Polyconnectomic scoring of functional connectivity patterns across eight neuropsychiatric and three neurodegenerative disorders.

Background: Neuropsychiatric and neurodegenerative disorders involve diverse changes in brain functional connectivity. As an alternative to approaches searching for specific mosaic patterns of affected connections and networks, we used polyconnectomic scoring to quantify disorder-related whole-brain connectivity signatures into interpretable, personalized scores.

Methods: The polyconnectomic score (PCS) measures the extent to which an individual's functional connectivity (FC) mirrors the whole-brain circuitry characteristics of a trait.

Quantifying brain connectivity signatures by means of polyconnectomic scoring.

A broad range of neuropsychiatric disorders are associated with alterations in macroscale brain circuitry and connectivity. Identifying consistent brain patterns underlying these disorders by means of structural and functional MRI has proven challenging, partly due to the vast number of tests required to examine the entire brain, which can lead to an increase in missed findings. In this study, we propose polyconnectomic score (PCS) as a metric designed to quantify the presence of disease-related brain connectivity signatures in connectomes.

Convergence of Brain Transcriptomic and Neuroimaging Patterns in Schizophrenia, Bipolar Disorder, Autism Spectrum Disorder, and Major Depressive Disorder.

Background: Psychiatric conditions show overlap in their symptoms, genetics, and involvement in brain areas and circuits. Structural alterations in the brain have been found to run in parallel with expression profiles of risk genes at the level of the brain transcriptome, which may point toward a potential transdiagnostic vulnerability of the brain to disease processes.

Methods: We characterized the transcriptomic vulnerability of the cortex across 4 major psychiatric disorders based on collated data from patients with psychiatric disorders (n = 390) and matched control participants (n = 293).

Statistical power in network neuroscience.

Network neuroscience has emerged as a leading method to study brain connectivity. The success of these investigations is dependent not only on approaches to accurately map connectivity but also on the ability to detect real effects in the data - that is, statistical power. We review the state of statistical power in the field and discuss sample size, effect size, measurement error, and network topology as key factors that influence the power of brain connectivity investigations.

Momentary effects of Temstem, an app for voice-hearing individuals: Results from naturalistic data from 1048 users.

Background: Temstem is a mobile application developed in cooperation with voice-hearing persons to help them cope with distressing voices. After psychoeducation about voice hearing, Temstem offers two functions: Silencing is a mode designed to inhibit voice activity through the processing of incompatible language; the Challenging mode introduces dual tasking (as used in eye movement desensitisation and reprocessing) designed to reduce the emotionality and vividness of a voice memory. Two different language games, Lingo Tapper and Word Link, are provided, containing both functions.